Dead-time effects result in a non-linear detector response in the common time-of-flight secondary-ion mass spectrometry instruments. This can result in image artifacts that can often be misinterpreted. Although the Poisson correction procedure has been shown to effectively eliminate this non-linearity in spectra, applying the correction to images presents difficulties because the low number of counts per pixel can create large statistical errors. The efficacy of three approaches to dead-time correction in images has been explored. These approaches include: pixel binning, image segmentation and a binomial statistical correction. When few pixels are fully saturated, all three approaches work satisfactorily. When a large number of pixels are fully saturated, the statistical approach fails to remove the dead-time artifacts revealed by multivariate analysis. Pixel binning is accurate at higher levels of saturation so long as the bin size is much smaller than the feature size. The segmentation approach works well independent of feature size or the number of fully saturated pixels but requires an accurate segmentation algorithm. It is recommended that images be collected under conditions that minimize the number of fully saturated pixels. When this is impractical and small features are present in the image, segmentation can provide an accurate way to correct for the detector saturation effect. Copyright © 2012 John Wiley & Sons, Ltd.